This presentation shows how Dynamic Map Platform’s high‑precision 3D data – point clouds, imagery, trajectories and annotated HD maps – accelerates safe and scalable development of ADAS and end‑to‑end autonomous driving. DMP provides over 1,800,000km of global road coverage, enabling diverse real‑world scenarios for training and validation across regions and road types. Supporting OpenDrive and native simulation formats, the data integrates seamlessly with various simulation platforms. Combined with 3D Gaussian splatting, it enables fast, photorealistic digital‑twin generation and scenario‑based, closed‑loop testing, addressing efficiency and coverage challenges in autonomous system development for OEMs and Tier 1 suppliers targeting production‑ready validation at scale.

• How DMP’s global, centimeter‑accurate 3D data enables robust ADAS and E2E development across diverse regions, road types and real‑world driving environments
• Why large‑scale real‑world datasets are critical for capturing rare, safety‑critical edge cases that are difficult or costly to collect worldwide
• How DMP data supports OpenDrive and other native formats, enabling seamless integration with simulation platforms used by OEMs and Tier 1 suppliers
• How 3D Gaussian splatting reconstructs photorealistic digital‑twin environments quickly and accurately, preserving real‑world fidelity at scale
• How high‑fidelity scenario generation improves closed‑loop testing efficiency, validation coverage and development speed for production‑ready systems